activity
20182021
most citedMicro-UAV Detection and Classification from RF Fingerprints Using Machine Learning Techniques

1 citations · 1 across the 6 of their papers we have counts for

collaborators

15 papers

eess.SP2021

Radar Cross Section Based Statistical Recognition of UAVs at Microwave Frequencies

Martins Ezuma, Chethan Kumar Anjinappa, Mark Funderburk +1

This paper presents a radar cross-section (RCS)-based statistical recognition system for identifying/ classifying unmanned aerial vehicles (UAVs) at microwave frequencies. First, t…

eess.SP2020

Base Station and Passive Reflectors Placement for Urban mmWave Networks

Chethan Kumar Anjinappa, Fatih Erden, Ismail Guvenc

The use of millimeter-wave (mmWave) bands in 5G networks introduce a new set of challenges to network planning. Vulnerability to blockages and high path loss at mmWave frequencies…

eess.SP2020

Outdoor mmWave Base Station Placement: A Multi-Armed Bandit Learning Approach

Fatih Erden, Chethan K. Anjinappa, Ender Ozturk +1

Base station (BS) placement in mobile networks is critical to the efficient use of resources in any communication system and one of the main factors that determines the quality of…

eess.SP2020

Localization with Deep Neural Networks using mmWave Ray Tracing Simulations

Udita Bhattacherjee, Chethan Kumar Anjinappa, LoyCurtis Smith +2

The world is moving towards faster data transformation with more efficient localization of a user being the preliminary requirement. This work investigates the use of a deep learni…

eess.SP2019

Off-Grid Aware Spatial Covariance Estimation in mmWave Communications

Chethan Kumar Anjinappa, Ali Cafer Gurbuz, Yavuz Yapici +1

This work investigates the problem of spatial covariance matrix estimation in a millimeter-wave (mmWave) hybrid multiple-input multiple-output (MIMO) system with an emphasis on the…

eess.SP2019

Detection and Classification of UAVs Using RF Fingerprints in the Presence of Interference

Martins Ezuma, Fatih Erden, Chethan Kumar Anjinappa +2

This paper investigates the problem of detection and classification of unmanned aerial vehicles (UAVs) in the presence of wireless interference signals using a passive radio freque…